INDUSTRY 4.0: HOW GLOBAL BIOPHARMA COMPANY REALIZES 50% INCREASE IN RATE OF DRUG DEVELOPMENT

You are better off looking at data than looking for data.

About the company

  • Objective: Implement new initiatives in the production process
  • Industry: BioPharma
  • Result: Structured access to data increase rate of drug development and cost savings
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The Background

The R&D biopharma facility of one of our key Global clients, who’s a key player in the rare diseases space in the US, were generating, processing and storing data in a complicated series of networks and standalone data islands. There was no ‘single source of truth’ with regards to their data plan. Their Data Strategy was not defined, and each platform was a customized solution resulting in increased timelines and costs in deployment and maintainability.

The Challenge

In addition to having complex data strategy challenges, they were also faced with 4 other areas of concern namely:

  • Visualizations: were only available on the plant floor and viewed through the PCS system software. The Operators’ desks were a 5 minute walk away from these
  • Alarming platform: which was part of their DCS system was reaching end-of-life and needed replacement.
  • Reports: consisted of spreadsheets & manual data entry.
  • Offline Analyzer: information was not linked to batch data

Complex searches required to gather specific data on batches with manual input required for reporting.

Reduced time it took to get a new drug through from conception to clinical trials.
Competitive advantage in getting to market over competitors.
Scientists to analyse an experiment in 10 minutes or less.
Facility realized a 50% increase over their previous rate of drug development.

The Solution

A strategy for automated data collection

To address the data strategy challenges, a PI Core System was deployed in a Development/Sandbox environment.

The first part of this was the Development system which consisted of the PI Core elements such as the PI Data Archive, AF, Analytics, Notifications, PI Vision and RtReports.

Next, we deployed a PI Core System for Production which was documented and validated. This was a larger version of the Development system and included an application per server.

Finally, to pull in data from source systems, we completed a system readiness study.

The Results

Data Analytics Is An Important Tool For Optimization

The facility realized an amazing 50% increase over their previous rate of drug development. As a result, 6 research programs instead of 4
were undertaken during the same period.

From a cost perspective, there were significant reduced time in getting a new drug through from conception to clinical trials, which are costly and time consuming. Expensive audit findings were spared, and Scientists could analyse an experiment in 10 minutes or less. This led to a competitive
advantage in getting to market first over competitors.

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